What Classes to Take to Become a Machine Learning Engineer

A machine learning engineer uses programming to design and build software that is used in artificial intelligence and machine learning. They play a large role in gathering and processing data, and developing algorithms that allow machine systems to learn from themselves. If you’re ready to join the world of machine learning, training is a must. With the growing influence of machine learning in nearly every industry that uses technology, taking a course can help you build up your professional credentials with the help of a strong network, an active portfolio, and hands-on experience in the field. This article reviews the ideal courses for an up-and-coming machine learning engineer, highlighting various class types and how they can impact your overall educational goals in machine learning.

Workshops, Seminars, One-Day Classes, and Short Courses

Workshops and seminars are breif, hands-on sessions that often highlight a specific topic in machine learning. They are great for beginners who want to focus on fundamental or introductory skills. This course type is great for networking, which is especially relevant in a rapidly growing field like machine learning or artificial intelligence. Workshops can be found at many institutions, and are an ideal choice for those looking to gain specialized experience in a specific tool, technique, or aspect of machine learning. Seminars are panel discussions led by industry professionals, and can frequently be found at conferences or universities. These can be a great opportunity to meet like-minded individuals and also learn more about up and coming technologies that will impact the world of machine learning. Workshops and seminars are relatively short, and though they are missing some of the professional components that a student would find in part-time and full-time classes, they are important for building confidence in those foundational skills before moving onto more advanced topics. They are also an ideal opportunity for those looking to fill gaps in their knowledge, or maintain practice with the skills that they already have.

One-day courses and other short courses last from a full day to a few weeks. Like workshops, one-day courses often focus on a specific part of machine learning, though they are considered an all day affair and often begin in the morning, and end in the evening. Short courses can vary more widely in length, and may start at a few days, going to a few weeks. These classes and programs often have a solid curriculum with overarching educational goals, though they are not as intensive or comprehensive as bootcamps, university classes, or certificate programs. When it comes to machine learning, a more advanced education is recommended, as the field is highly technical and requires a solid foundation in several relevant fields like data science, computer science, and artificial intelligence. However, short courses and one-day courses are great for upskilling, maintaining proficiency, or making sure that your information is up to date.

University Courses

A university or college is a great way to learn machine learning in an in-depth and comprehensive way. There are two different approaches at this level. The first is a full degree track, which includes an undergraduate or graduate degree in machine learning or a related field. The most common degrees are computer science and data science, though any major in science, technology, or math will help understand the principles of artificial intelligence better. Both undergraduate and graduate classes will have requirements outside of technology, which can help you develop an interdisciplinary approach to the field, but they require a larger time commitment and can be more expensive than other course types. While a degree isn’t required to become a machine learning engineer, it is highly advantageous to those entering the job market. The more formal endorsements you can add to your portfolio, the more likely you are to be considered for higher-level positions that have more strict requirements.

The second approach is to take individual courses through the university without obtaining a degree. In this case, universities and colleges will host classes and programs that are shorter or less committed than the years-long process of finishing a degree. These may be summer courses, weekend courses, or weeks long courses in the form of bootcamps and workshops. Much like other university courses, they can introduce topics that are not strictly related to machine learning, but technology as a whole. This will allow you to gain skills that are relevant in a multitude of industries. Universities can be accredited, which can make their endorsement even more valuable. Whether aiming for a degree or not, courses hosted by a university are an investment that can ultimately benefit your career, while helping you gain confidence in your programming, data, and machine learning skills.

Bootcamps, Certification Courses 

Bootcamps are intensive programs that focus more on practical skills and professional development than a traditional course. They are highly immersive and can help you grow your portfolio so that you can transition from your coursework to your career opportunities more easily. Bootcamps are valuable for machine learning engineers because they offer hands on experience with real-world projects. You’ll also have access to industry experts and like-minded peers who can become a part of your network. Some bootcamps offer career services that can help you with resume building and interview preparation. Though bootcamps are often tailored towards learners with experience, there are beginner bootcamps available. It’s important to double-check the curriculum prior to signing up to better understand any prerequisites.

Certification courses are slightly different. They are similarly intensive, but the overall goal is to help you gain certification in machine learning. Companies like Google, Microsoft, and IBM offer certification as an artificial intelligence or machine learning engineer. Certification acts as an endorsement of your skills, and can provide a massive boost in the professional world. Bootcamps will offer a certificate of completion, and though this can help pad your portfolio, it is different from certification. Certification aligns with industry standards, and often requires oversight from a reputable or accredited institution. A certificate is evidence of completion for a course taken. There is often testing involved with certification. Machine learning is closely related to other certified professions. You can become a Certified Data Scientist (CDS), or certified in Big Data. Both are closely related to machine learning, and will be useful in any industry that uses this technology.

Learn Machine Learning with Noble Desktop

Noble Desktop is a great place to start your machine learning journey. They offer a Python Data Science & Machine Learning Bootcamp which teaches the popular programming language Python, and ties it into the field of machine learning and automation. Python is a valuable skill even outside of artificial intelligence, and can be used in practically any industry that depends on technology. This bootcamp reviews Python for automation, data visualization, and interactive dashboards. This comprehensive course will also build your confidence in programming so that you’re not only ready for entry-level positions in data science and Python engineering, but capable of creating predictive models from data, and automating everyday tasks in a variety of fields. As you finish the course, you will receive a digital certificate of completion that you can add to your professional portfolio and digital profiles. 

For those who are more interested in the Data Science aspect of machine learning, Noble Desktop also has a Data Science Certificate. Machine learning engineers often take statistical or machine learning models developed by data scientists, so this particular course is highly relevant. This class reviews Python, SQL, automation, and machine learning, and includes three bootcamps, including the Python for Data Science bootcamp, Python Machine Learning Bootcamp, and SQL bootcamp. An attractive feature of this course for tech-minded individuals is the ability to create machine-learning models with data collected during the course.

There is also the option of taking an artificial intelligence course. Noble Desktop’s Generative AI with ChatGPT is highly relevant, and a great opportunity to enhance your overall understanding of the field. During the course, you can see machine learning in action, and contribute to one of this decade’s more popular artificial helpers: ChatGPT. Through this course, you’ll learn how to write prompts in a way that gives you useful feedback. You can also explore how the modern world is using technology like ChatGPT and similar bots to enhance their experiences and simplify their day-to-day lives.